2018/11/07 by Bastian Körtgen, Christoph Federrath, Robi Banerjee · 1 citation
Chemical Engineering · Mathematics · Physics and Astronomy · #Advanced Combustion Engine Technologies #Astro and Planetary Science #Astrophysics #Astrophysics and Star Formation Studies #Completeness (order theory) #Log-normal distribution #Mathematical analysis #Mathematics #Molecular cloud #Physics #Power law #Probability density function #Probability distribution #Star formation #Stars #Statistical physics #Statistics #astro-ph.GA
paper · pdf · doi:10.1093/mnras/sty3071
accepted for publication by MNRAS. 9 pages, 5 figures, comments welcome
arxiv created 2018/11/07 · openalex publication_date 2018/11/08 · openalex created_date 2018/11/16 · arxiv updated 2018/11/28 · openalex updated_date 2026/08/05
Both observational and theoretical research over the past decade has demonstrated that the probability distribution function (PDF) of the gas density in turbulent molecular clouds is a key ingredient for understanding star formation. It has recently been argued that the PDF of molecular clouds is a pure power-law distribution. It has been claimed that the log-normal part is ruled out when using only the part of the PDF up/down to which it is complete, that is where the column density contours are still closed. By using the results from high-resolution magnetohydrodynamical simulations of molecular cloud formation and evolution, we find that the column density PDF is indeed composed of a log-normal and, if including self-gravity, a power-law part. We show that insufficient sampling of a molecular cloud results in closed contours that cut-off the log-normal part. In contrast, systematically increasing the field of view and sampling the entire cloud yields a completeness limit at the lower column densities, which also recovers the log-normal part. This demonstrates that the field of view must be sufficiently large for the PDF to be complete down to its log-normal part, which has important implications for predictions of star formation activity based on the PDF.